Plasma fibronectin depletion enhances platelet aggregation and thrombus formation in mice lacking fibrinogen and von Willebrand factor
Bibliographic record
Abstract
We previously showed that platelet aggregation and thrombus formation occurred in mice lacking both fibrinogen (Fg) and von Willebrand factor (VWF) and that plasma fibronectin (pFn) promoted thrombus growth and stability in injured arterioles in wild-type mice. To examine whether pFn is required for Fg/VWF-independent thrombosis, we generated Fg/VWF/conditional pFn triple-deficient (TKO; Cre(+), Fn(flox/flox), Fg/VWF(-/-)) mice and littermate control (Cre(-), Fn(flox/flox), Fg/VWF(-/-)) mice. Surprisingly, TKO platelet aggregation was not abolished, but instead was enhanced in both heparinized platelet-rich plasma and gel-filtered platelets. This enhancement was diminished when TKO platelets were aggregated in pFn-positive control platelet-poor plasma (PPP), whereas aggregation was enhanced when control platelets were aggregated in pFn-depleted TKO PPP. The TKO platelet aggregation can be completely inhibited by our newly developed mouse anti-mouse beta(3) integrin antibodies but was not affected by anti-mouse GPIbalpha antibodies. Enhanced platelet aggregation was also observed when heparinized TKO blood was perfused in collagen-coated perfusion chambers. Using intravital microscopy, we further showed that thrombogenesis in TKO mice was enhanced in both FeCl(3)-injured mesenteric arterioles and laser-injured cremaster arterioles. Our data indicate that pFn is not essential for Fg/VWF-independent thrombosis and that soluble pFn is probably an important inhibitory factor for platelet aggregation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".